Semi-automatic ground truth annotation in videos
Julius Schöning, Patrick Faion, Gunther Heidemann · 2015
Knowledge extraction from video data is challenging due to its high complexity in both the spatial and temporal domain. Ground truth is crucial for the evaluation and the adaptation of algorithms to new domains. Unfortunately, ground truth annotation is inconvenient and time consuming. Common annotation tools mostly rely on simple geometric primitives such as rectangles or ellipses. Here we propose a novel, interactive and semi-automatic process, which actively asks for user input if the result of the automatic annotation appears to be incorrect. After a brief review of related tools for video annotation, we explain our proposed semi-automatic method iSeg using a prototype implementation. iSeg has been tested on two visual stimulus datasets for eye tracking experiments and on two surveillance datasets. The experimental results and the usability are compared to existing annotation tools. Finally, we discuss the properties and opportunities of polygon-based video annotation.